Tool condition monitoring is critical in ultraprecision manufacturing in order to optimize the performance of the overall process, while maintaining the desired part quality. Recently, deep learning ...has been successfully applied to numerous classification tasks in manufacturing, often to forecast part quality. In this paper, a novel deep learning data-driven modeling framework is presented, which includes a fusion of multiple stacked sparse autoencoders for tool condition monitoring in ultraprecision machining. The proposed computational framework consists of two main structures. First, a training model that is designed with the ability to process multiple parallel feature spaces to learn the lower-level features. Second, a feature fusion structure that is used to learn the higher-level features and associations to tool wear. To achieve this learning structure, a modified loss function is utilized that enhances the feature extraction and classification tasks. A dataset from a real manufacturing process is used to demonstrate the performance of the proposed framework. Experimental results and simulations show that the proposed method successfully classifies the ultraprecision machining case study with over 96% accuracy, while also outperforming comparable methodologies.
Exploration of high‐efficiency, economical, and ultrastable electrocatalysts for the oxygen reduction reaction (ORR) to substitute precious Pt is of great significance in electrochemical energy ...conversion devices. Single‐atom catalysts (SACs) have sparked tremendous interest for their maximum atom‐utilization efficiency and fascinating properties. Therefore, the development of effective synthetic methodology toward SACs becomes highly imperative yet still remains greatly challenging. Herein, a reliable SiO2‐templated strategy is elaborately designed to synthesize atomically dispersed Fe atoms anchored on N‐doped carbon nanospheres (denoted as Fe–N–C HNSs) using the cheap and sustainable biomaterial of histidine (His) as the N and C precursor. By virtue of the numerous atomically dispersed Fe–N4 moieties and unique spherical hollow architecture, the as‐fabricated Fe–N–C HNSs exhibit excellent ORR performance in alkaline medium with outstanding activity, high long‐term stability, and superior tolerance to methanol crossover, exceeding the commercial Pt/C catalyst and most previously reported non‐precious‐metal catalysts. This present synthetic strategy will provide new inspiration to the fabrication of various high‐efficiency single‐atom catalysts for diverse applications.
Atomically dispersed Fe atoms anchored on N‐doped carbon nanospheres (denoted as Fe–N–C HNSs) are synthesized via a reliable hard‐template‐engaged approach. Owing to the abundant atomically dispersed Fe–N4 moieties and distinct spherical hollow architecture, the developed Fe–N–C HNSs exhibit remarkably improved electrocatalytic performance for the oxygen reduction reaction, as compared with commercial Pt/C catalyst.
Summary
Aims
Brain ischemia activates astrocytes in a process known as astrogliosis. Although this process has beneficial effects, excessive astrogliosis can impair neuronal recovery. ...Polyinosinic–polycytidylic acid (Poly IC) has shown neuroprotection against cerebral ischemia–reperfusion injury, but whether it regulates reactive astrogliosis and glial scar formation is not clear.
Methods
We exposed cultured astrocytes to oxygen–glucose deprivation/reoxygenation (OGD/R) and used a rat middle cerebral artery occlusion (MCAO)/reperfusion model to investigate the effects of Poly IC. Astrocyte proliferation and proliferation‐related molecules were evaluated by immunostaining and Western blotting. Neurological deficit scores, infarct volumes and neuroplasticity were evaluated in rats after transient MCAO.
Results
In vitro, Poly IC inhibited astrocyte proliferation, upregulated Toll‐like receptor 3 (TLR3) expression, upregulated interferon‐β, and downregulated interleukin‐6 production. These changes were blocked by a neutralizing antibody against TLR3, suggesting that Poly IC function is TLR3‐dependent. Moreover, in the MCAO model, Poly IC attenuated reactive astrogliosis, reduced brain infarction volume, and improved neurological function. In addition, Poly IC prevented MCAO‐induced reductions in soma size, dendrite length, and number of dendritic bifurcations in cortical neurons of the infarct penumbra.
Conclusions
By ameliorating astrogliosis‐related damage, Poly IC is a potential therapeutic agent for attenuating neuronal damage and promoting recovery after brain ischemia.
Blockchain technology is a widely used emerging technology. It can integrate cloud computing technology and big data to form a distributed cloud computing system, providing efficient services for ...local enterprises and governments. In addition, local cloud computing is also widely used, and there are many big data in these applications. Blockchain and local cloud computing technology offers safe and reliable information exchange for data exchange and provides a practical method for analyzing big data. This article aims to study how to analyze and research the application analysis method of big data based on blockchain technology and improve the classical apriori algorithm (CAA). This article compares and analyzes the performance of CAA and improved apriori algorithm (IAA) in big data applications. When the number of key words in the query are 20 and 100, the result search time of the CAA are 1.08 and 9.24 s, respectively, and the IAA are 0.76 and 7.58 s, respectively. The result search cost of the CAA is 12.43 and 91.55 kB, respectively, and the IAA is 5.05 and 63.72 kB, respectively. It is not difficult to see that applying the IAA to the blockchain-based government data-sharing scheme had relatively excellent performance and was worth further promotion and application.
Phase change memory (PCM) is an emerging non‐volatile data storage technology concerned by the semiconductor industry. To improve the performances, previous efforts have mainly focused on partially ...replacing or doping elements in the flagship Ge‐Sb‐Te (GST) alloy based on experimental “trial‐and‐error” methods. Here, the current largest scale PCM materials searching is reported, starting with 124 515 candidate materials, using a rational high‐throughput screening strategy consisting of criteria related to PCM characteristics. In the results, there are 158 candidates screened for PCM materials, of which ≈68% are not employed. By further analyses, including cohesive energy, bond angle analyses, and Born effective charge, there are 52 materials with properties similar to the GST system, including Ge2Bi2Te5, GeAs4Te7, GeAs2Te4, so on and other candidates that have not been reported, such as TlBiTe2, TlSbTe2, CdPb3Se4, etc. Compared with GST, materials with close cohesive energy include AgBiTe2, TlSbTe2, As2Te3, TlBiTe2, etc., indicating possible low power consumption. Through further melt‐quenching molecular dynamic calculation and structural/electronic analyses, Ge2Bi2Te5, CdPb3Se4, MnBi2Te4, and TlBiTe2 are found suitable for optical/electrical PCM applications, which further verifies the effectiveness of this strategy. The present study will accelerate the exploration and development of advanced PCM materials for current and future big‐data applications.
Phase‐change memory (PCM) is a state‐of‐the‐art nonvolatile data memory technology depending on transitions between amorphous and crystalline phases of PCM materials. To explore advanced material candidates, the current largest scale material searching is carried out using a rational high‐throughput screening strategy consisting of criteria related to PCM characteristics. A series of unreported materials are found potentially suitable for PCM applications.
Immunoglobulin A (IgA) nephropathy (IgAN), the most common form of glomerulonephritis, is one of the leading causes of end-stage kidney disease (ESKD). It is widely believed that genetic factors play ...a significant role in the development of IgAN. Previous studies of IgAN have provided important insights to unravel the genetic architecture of IgAN and its potential pathogenic mechanisms. The genome-wide association studies (GWASs) together have identified over 30 risk loci for IgAN, which emphasizes the importance of IgA production and regulation in the pathogenesis of IgAN. Follow-up fine-mapping studies help to elucidate the candidate causal variant and the potential pathogenic molecular pathway and provide new potential therapeutic targets. With the rapid development of next-generation sequencing technologies, linkage studies based on whole-genome sequencing (WGS)/whole-exome sequencing (WES) also identify rare variants associated with IgAN, accounting for some of the missing heritability. The complexity of pathogenesis and phenotypic variability may be better understood by integrating genetics, epigenetics, and environment. We have compiled a review summarizing the latest advancements in genetic studies on IgAN. We similarly summarized relevant studies examining the involvement of epigenetics in the pathogenesis of IgAN. Future directions and challenges in this field are also proposed.
Saliency detection is used to identify the most important and informative area in a scene, and it is widely used in various vision tasks, including image quality assessment, image matching, and ...object recognition. Manifold ranking (MR) has been used to great effect for the saliency detection, since it not only incorporates the local spatial information but also utilizes the labeling information from background queries. However, MR completely ignores the feature information extracted from each superpixel. In this paper, we propose an MR-based matrix factorization (MRMF) method to overcome this limitation. MRMF models the ranking problem in the matrix factorization framework and embeds query sample labels in the coefficients. By incorporating spatial information and embedding labels, MRMF enforces similar saliency values on neighboring superpixels and ranks superpixels according to the learned coefficients. We prove that the MRMF has good generalizability, and develops an efficient optimization algorithm based on the Nesterov method. Experiments using popular benchmark data sets illustrate the promise of MRMF compared with the other state-of-the-art saliency detection methods.
AbstractA detailed seismic performance assessment for super high-rise buildings is essential for decision-making on postearthquake repair, maintenance, and reoccupation. This paper proposes a ...probabilistic assessment framework for instrumented super high-rise buildings under bidirectional long-period ground motions in which the probabilities of key structural components experiencing different damage levels are assessed. The fragility curves of the key structural components are obtained by performing a nonlinear incremental dynamic analysis on the building model. The evolving mean values and variances of the structural responses are determined by using the Kalman smoothing algorithm based on the integrated optimal sensor placement and response reconstruction scheme. The extreme value distribution of the structural responses is obtained in terms of the Vanmarcke approximation and then incorporated with generated fragility curves to yield an estimation of the probabilistic damage states of the key structural components. The proposed framework is finally applied to a real super high-rise building, and the results manifest that the proposed framework provides a reliable way of estimating the safety and operability levels of the instrumented building after the earthquake event.
The lateral parabrachial nucleus (LPBN) is known to relay noxious information to the amygdala for processing affective responses. However, it is unclear whether the LPBN actively processes ...neuropathic pain characterized by persistent hyperalgesia with aversive emotional responses. Here we report that neuropathic pain-like hypersensitivity induced by common peroneal nerve (CPN) ligation increases nociceptive stimulation-induced responses in glutamatergic LPBN neurons. Optogenetic activation of GABAergic LPBN neurons does not affect basal nociception, but alleviates neuropathic pain-like behavior. Optogenetic activation of glutamatergic or inhibition of GABAergic LPBN neurons induces neuropathic pain-like behavior in naïve mice. Inhibition of glutamatergic LPBN neurons alleviates both basal nociception and neuropathic pain-like hypersensitivity. Repetitive pharmacogenetic activation of glutamatergic or GABAergic LPBN neurons respectively mimics or prevents the development of CPN ligation-induced neuropathic pain-like hypersensitivity. These findings indicate that a delicate balance between excitatory and inhibitory LPBN neuronal activity governs the development and maintenance of neuropathic pain.
Oxidase‐mimicking nanozymes are more desirable than peroxidase‐mimicking ones since H2O2 can be omitted. However, only a few nanomaterials are known for oxidase‐like activities. In this work, we ...compared the activity of Mn2O3, Mn3O4 and MnO2 and found that Mn2O3 had the highest oxidase activity. Interestingly, the activity of Mn2O3 was even inhibited by H2O2. The oxidase‐like activity of Mn2O3 was not much affected by the presence of proteins such as bovine serum albumin (BSA), but the physisorption of antibodies to Mn2O3 was not strong enough to withstand the displacement by BSA. We then treated Mn2O3 with 3‐aminopropyltriethoxysilane to graft an amine group, which was used to conjugate antibodies using glutaraldehyde as a crosslinker. A one‐step indirect competitive ELISA (icELISA) was developed for the detection of isocarbophos, and an IC50 of 261.7 ng/mL was obtained, comparable with the results of the standard two‐step assay using horseradish peroxidase (HRP)‐labeled antibodies. This assay has the advantage of significant timesaving for rapid detection of large amounts of samples. This work has discovered a highly efficient oxidase‐mimicking nanozyme useful for various nano‐ and analytical applications.
Mn2O3 nanoparticles have the highest oxidase‐like activity among the tested metal oxides, but the activity is inhibited by H2O2. Mn3O4 behaves similarly, while the activity of MnO2 is enhanced by H2O2.
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